Abstract: A displacement measuring apparatus measures a displacement of a measurement object by using a captured image where the measurement object and a load object are imaged. The displacement is caused by the load object in contact with the measurement object at a contact position. The displacement measuring apparatus includes a position detector, an area setting unit and a displacement calculator. The position detector detects a position, of the load object, in the captured image. The area setting unit sets a position and a size of a detection area in the captured image by using distance information and the position of the load object detected by the position detector, the distance information spatially indicating a distance between the measurement object when the load object is not on the measurement object and an imaging device that generates the captured image. The displacement calculator calculates the displacement by using only an image in the detection area in the captured image.

Abstract: The present disclosure relates to a target detection method and device, a computing device and a readable storage medium. The target detection method include performing target detection using a convolutional neural network comprising a plurality of convolutional layers. The method include performing a branch convolutional process on at least one of the convolutional layers to obtain a branch detection result. The method includes performing a fusion process on the branch detection result, or on the branch detection result and a detection result of a last convolutional layer in the convolutional neural network, and transmitting a result of the fusion process to a fully connected layer.

Abstract: In a data processing method executed by a computer: inputting, in a third trained model, first output data corresponding to first input data for a first trained model to obtain second output data, the third trained model being acquired through training in which (i) output data of the first trained model is used as training data, and (ii) output data of a second trained model acquired by converting the first trained model is used as label data; obtaining first label data of the first input data; and retraining the first trained model using first differential data corresponding to differences between the second output data and the first label data.

Abstract: Systems and methods for Optical Character Recognition (“OCR”) based anti-spoofing for Unicode homograph. The method comprises: performing operations by a computing device to make an OCR identification on an original electronic address so as to obtain an OCR electronic address; encoding (a) the original electronic address to obtain an encoded access address and (b) the OCR electronic address to obtain an encoded OCR electronic address; comparing the encoded access address to the encoded OCR electronic address; and determining if a Unicode homograph spoofing situation exists based on results of the comparing.

Abstract: A storage unit stores at least one first analysis result generated by performing at least one first analysis process on an image of a subject and recovery information enabling recovery of a first analysis state where the first analysis result is generated or link information to the recovery information in a database in association with subject information specifying the subject. An analysis unit generates, in a case where at least one second analysis process generating at least one second analysis result different from the first analysis result is performed, the second analysis result by performing the second analysis process using the recovery information. The storage unit stores the second analysis result in the database in association with the subject information.

Abstract: A method and apparatus for evaluating an illumination condition in a face image is provided by decomposing a face image into illumination feature components and face feature components; extracting determined areas in the face image; calculating a maximum luminance feature, a minimum luminance feature and an illumination direction feature according to the decomposed illumination feature components in the determined areas. The illumination condition in the face image is evaluated according to the maximum luminance feature, the minimum luminance feature and the illumination direction feature.

Abstract: A method for identifying a mask for a patient includes: receiving a plurality of images of a patient's face; analyzing the plurality of images to generate a temporal model of the patient's face, determining a mask for the patient using the temporal model of the patient's face, and identifying the mask to the patient.

Abstract: Techniques for demosaicing of digital color images are improved by estimating and using the structural instability in the neighborhood of the respective pixel. The structural instability for a color is given by the range of the color values for this color in a first local region around each current pixel. A method is executed by a device for interpolating a missing color at the current pixel in a color image produced by a digital image sensor having a color filter array, the current pixel having a current color that differs from the missing color. The method comprises: computing (51) a range value for one of: pixels having the missing color and pixels having the current color; computing (52) an interpolation value at the current pixel as a function of the range value and color values for pixels having the missing color within a second local region around the current pixel; and setting the missing color at the current pixel to the interpolation value.

Abstract: A biological information measurement device includes: an information input request unit configured to request an input of identification information at each of a plurality of timings after measurement of the biological information is started; a personal identification unit configured to determine whether a user wearing the biological information measurement device is a pre-registered person in synchronization with each of the plurality of timings, based on the identification information; an identification result information generation unit configured to generate identification result information indicative of a relationship between a first number of times that the request is made by the information input request unit and a second number of times that the user is determined to be the pre-registered person by the personal identification unit; and a correctness determination unit configured to determine correctness of the biological information on the basis of the identification result information.

Abstract: A system and method for binocular stereo vision is disclosed. The method includes acquiring a pair of images including a first image and a second image, the pair of images being captured by one or more cameras; obtaining a training model; determining a plurality of feature images according to the first image; determining one or more features of an object in the first image according to the training model and the plurality of feature images; determining a first area in the first image, the first area including at least one of the determined one or more features; obtaining depth information of the determined first area based on the first and second images; and determining a second area in the first image based on the determined first area and depth information, the second area including at least one of the determined first area.

Abstract: By using a character recognition result of a scan image, a user can set supplementary information such as a file name for the scan image with simple operation.

Abstract: A method and an apparatus for reconstructing a hyperspectral image using artificial intelligence are provided. The method includes receiving an encoded sensor input for an image and reconstructing a hyperspectral image of the image for the encoded sensor input based on a previously generated nonlinear learning model.

Abstract: The technology disclosed presents a novel spatial attention model that uses current hidden state information of a decoder long short-term memory (LSTM) to guide attention and to extract spatial image features for use in image captioning. The technology disclosed also presents a novel adaptive attention model for image captioning that mixes visual information from a convolutional neural network (CNN) and linguistic information from an LSTM. At each timestep, the adaptive attention model automatically decides how heavily to rely on the image, as opposed to the linguistic model, to emit the next caption word. The technology disclosed further adds a new auxiliary sentinel gate to an LSTM architecture and produces a sentinel LSTM (Sn-LSTM). The sentinel gate produces a visual sentinel at each timestep, which is an additional representation, derived from the LSTM's memory, of long and short term visual and linguistic information.

Abstract: Embodiments predict early stage NSCLC recurrence, and include processors configured to access a pathology image of a region of tissue demonstrating early stage NSCLC; extract a set of pathomic features from the pathology image; access a radiological image of the region of tissue; extract a set of radiomic features from the radiological image; generate a combined feature set that includes at least one member of the set of pathomic features, and at least one member of the set of radiomic features; compute a probability that the region of tissue will experience NSCLC recurrence based, at least in part, on the combined feature set; and classify the region of tissue as recurrent or non-recurrent based, at least in part, on the probability. Embodiments may display the classification, or generate a personalized treatment plan based on the classification.

Abstract: In various embodiments, a reconstruction application generates reconstructed video content that includes synthesized film grain. The reconstruction application performs scaling operation(s) on first unit noise based on a piecewise linear scaling function and the brightness component of the decoded video content to generate a brightness component of synthesized film grain. The reconstruction application then generates a brightness component of reconstructed video content based on the brightness component of the synthesized film grain and the brightness component of the decoded video content. Finally, the reconstructed application performs operation(s) related to saving the reconstructed video content to a file and/or further processing the reconstructed video content. Advantageously, the synthesized film grain reliably represents the film grain included in source video content from which the decoded video content was derived.

Abstract: A detection device adds, with regard to each of a plurality of sets of time-series data including a plurality of items, a time-shift term to at least any of the plurality of items included in each of the plurality of sets of time-series data. The detection device generates a plurality of attractors from the plurality of sets of time-series data to which the time-shift term has been added. The detection device generates a plurality of Betti sequences from each of the plurality of attractors by executing a persistent homology transformation on each of the plurality of attractors, each of the plurality of Betti sequences indicating a correspondence relationship between a Betti number and a scale value has been used for the persistent homology transformation. The detection device detects a state change in the plurality of sets of time-series data based on a time change in the plurality of Betti sequences.

Abstract: An apparatus includes a memory; a processor coupled to the memory, wherein the processor acquires three-dimensional information of observation points on an object from a sensor, specifies a first area and second areas adjacent to the first area from areas of the object based on the three-dimensional information, and specifies positions of feature points included in the second areas; sets links based on the feature points included in the second areas to estimate positions of skeletons included in the second areas; and uses end points of the skeletons and lengths from the end points of the skeletons to a position of a part included in the first area among parameters used to specify the position of the part, specifies the position of the part included in the first area, and estimates a position of a skeleton included in the first area based on the specified position of the part.

Abstract: Inputting an image to a neural network, performing convolution on a current frame included in the image to calculate a current feature map, which is a feature map at a present time, combining a past feature map, which is obtained by performing convolution on a past frame included in the image, and the current feature map, estimating an object candidate area using the combined past feature map and current feature map, estimating positional information and identification information regarding the one or more objects included in the current frame using the combined past feature map and current feature map and the estimated object candidate area, and outputting the positional information and the identification information regarding the one or more objects included in the current frame of the image estimated in the estimating as object detection results are included.

Abstract: A system and method for maintaining image integrity in a containerized environment. Image layers of a software container are scanned for metadata. The metadata is indexed and contextual metadata is added. Execution of the containerized environment is monitored to detect new image layers being executed. Integrity of images in the environment is maintained based on integrity rules and the metadata of each image layer. The integrity rules ensure image integrity by ensuring that pulled images are composed from trusted images, image layers are pushed by trusted users, image layers do not include potential vulnerabilities, and image layers do not override specific file paths. Trusted image layers may be automatically detected using a machine learning model trained based on historical image layer metadata.

Abstract: Embodiments of the present invention provide a wireless communication method and a device. The wireless communication method includes: determining, by a base station, a transmission mode used to send data to a terminal in a current scheduling period, where the transmission mode is one of a paired transmission mode or a non-paired transmission mode; and sending, by the base station to the terminal, information indicating a terminal type corresponding to the transmission mode. According to the method and device, the terminal may perform corresponding processing according to the transmission mode, thereby improving processing efficiency. For example, the terminal may select an adaptive receiving algorithm to demodulate a signal, to improve demodulation efficiency and accuracy.